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Perception of motion salience shapes the emergence of collective motions

Author

Listed:
  • Yandong Xiao

    (National University of Defense Technology)

  • Xiaokang Lei

    (Xi’an University of Architecture and Technology)

  • Zhicheng Zheng

    (Northwestern Polytechnical University)

  • Yalun Xiang

    (Northwestern Polytechnical University)

  • Yang-Yu Liu

    (Brigham and Women’s Hospital and Harvard Medical School
    University of Illinois at Urbana-Champaign)

  • Xingguang Peng

    (Northwestern Polytechnical University)

Abstract

Despite the profound implications of self-organization in animal groups for collective behaviors, understanding the fundamental principles and applying them to swarm robotics remains incomplete. Here we propose a heuristic measure of perception of motion salience (MS) to quantify relative motion changes of neighbors from first-person view. Leveraging three large bird-flocking datasets, we explore how this perception of MS relates to the structure of leader-follower (LF) relations, and further perform an individual-level correlation analysis between past perception of MS and future change rate of velocity consensus. We observe prevalence of the positive correlations in real flocks, which demonstrates that individuals will accelerate the convergence of velocity with neighbors who have higher MS. This empirical finding motivates us to introduce the concept of adaptive MS-based (AMS) interaction in swarm model. Finally, we implement AMS in a swarm of ~102 miniature robots. Swarm experiments show the significant advantage of AMS in enhancing self-organization of the swarm for smooth evacuations from confined environments.

Suggested Citation

  • Yandong Xiao & Xiaokang Lei & Zhicheng Zheng & Yalun Xiang & Yang-Yu Liu & Xingguang Peng, 2024. "Perception of motion salience shapes the emergence of collective motions," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-49151-x
    DOI: 10.1038/s41467-024-49151-x
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    References listed on IDEAS

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    1. Dario Floreano & Robert J. Wood, 2015. "Science, technology and the future of small autonomous drones," Nature, Nature, vol. 521(7553), pages 460-466, May.
    2. Manuel Sebastian Mariani & Zhuo-Ming Ren & Jordi Bascompte & Claudio Juan Tessone, 2019. "Nestedness in complex networks: Observation, emergence, and implications," Papers 1905.07593, arXiv.org.
    3. Máté Nagy & Zsuzsa Ákos & Dora Biro & Tamás Vicsek, 2010. "Hierarchical group dynamics in pigeon flocks," Nature, Nature, vol. 464(7290), pages 890-893, April.
    4. Hangjian Ling & Guillam E. Mclvor & Joseph Westley & Kasper Vaart & Richard T. Vaughan & Alex Thornton & Nicholas T. Ouellette, 2019. "Behavioural plasticity and the transition to order in jackdaw flocks," Nature Communications, Nature, vol. 10(1), pages 1-7, December.
    5. Serguei Saavedra & Felix Reed-Tsochas & Brian Uzzi, 2009. "A simple model of bipartite cooperation for ecological and organizational networks," Nature, Nature, vol. 457(7228), pages 463-466, January.
    6. Gaurav Gardi & Steven Ceron & Wendong Wang & Kirstin Petersen & Metin Sitti, 2022. "Microrobot collectives with reconfigurable morphologies, behaviors, and functions," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
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